Integrated Single-Cell RNA-Seq of Cancer Cells Under Immune Checkpoint Blockade

Eight compiled single-cell RNA-sequencing datasets from nine cancer types provide a resource of 90,270 cancer cells and over 265,000 other cells from 223 patients treated with immune checkpoint blockade. This integration allows cross-cancer investigation of cell-specific treatment responses, which are variable across patients and cancer types. The data is curated, pre-processed, and accompanied by a user-friendly exploration interface to lower the barrier for analysis.

Use Cases

• Identifying cancer cell transcriptional signatures associated with treatment response based on single-cell gene expression profiles.
• Comparing immune cell infiltration and state across different cancer types under immune checkpoint blockade.
• Benchmarking computational methods for single-cell data integration and analysis using a curated, multi-study resource.
• Investigating receptor and gene expression patterns in T cells and other immune cells from treated patients.

Strengths

• Compiles data from 223 patients across nine cancer types, providing a cross-cancer perspective.
• Includes detailed curation of 90,270 cancer cells and over 265,000 other cell types, enabling cell-type-specific analysis.
• Data is quality-checked, pre-processed, and accompanied by an exploration interface to facilitate use.

Limitations

• Sources conflict on patient count (174 vs 223), creating uncertainty about the exact cohort size.
• Column names and specific data structure are not provided, limiting understanding of the available features.
• The last update date and exact file formats are unknown, affecting assessment of data freshness and usability.

Provenance

Source

Mahnoor Gondal, University of Michigan

Collection Method

Compilation and curation of eight existing single-cell RNA-sequencing studies from patients treated with immune checkpoint blockade.